Create MCP TypeScript server with tools, testing, debugging, and best practices for efficient development
The MCP Server Template provides a comprehensive foundation for developing Model Context Protocol (MCP) compatible servers, allowing developers to integrate their tools seamlessly into AI applications such as Claude Desktop, Continue, and Cursor. This template leverages TypeScript, ensuring robust type safety and maintainability while offering advanced features like container-based dependency injection and service-oriented architecture.
The template is designed with full TypeScript support from the ground up, making it easier to manage complex data structures, interfaces, and handlers. This ensures that your codebase remains clean, easily understandable, and maintainable over time.
This feature allows for modular development by encapsulating individual components and services as separate containers. Each tool or service can be developed independently without impacting others, promoting a highly decoupled architecture.
The template adopts a service-oriented architecture centered around the DataProcessor
interface, enabling consistent and reliable data processing pipelines for various tools. This design facilitates easy updates to specific components without affecting the entire system.
By providing an example tool implementation complete with tests, users can quickly understand how to start building their own tools while ensuring they maintain high-quality standards through robust testing practices.
Vitest is a lightweight yet powerful testing framework tailored for modern JavaScript applications. It supports incremental rendering and supports both unit and integration tests, making it an ideal choice for comprehensive test coverage.
Type definitions are included to provide clear guidelines on the expected input and output types of your tools, enhancing code readability and reducing potential bugs.
The template seamlessly integrates with the Model Context Protocol (MCP) SDK, allowing developers to easily define and expose their tools according to the protocol requirements. This ensures compatibility across different AI applications that support MCP.
At its core, the MCP architecture revolves around the concept of standardized interaction between AI applications and data sources/tools through a well-defined protocol. The provided template takes meticulous care in implementing this protocol, ensuring seamless communication between the client and server.
Below is a visual representation of the MCP protocol flow diagram:
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[MCP Server]
C --> D[Data Source/Tool]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#e8f5e8
To fully understand the data architecture, consider the following diagram:
graph LR
subgraph AI Application [AI Application]
A[Initiate Request] --> B(MCP Client)
end
subgraph MCP Server [MCP Server]
C[MCP Protocol Handler] -- Process --> D(Response Preparation)
D --> E[Data Source/Tool]
end
To get started, follow these steps:
Install Dependencies
npm install
Start the Development Server
npm run dev
Build the Project
npm run build
Run Tests
npm test
Start the Production Server
npm start
Imagine a financial analyst using an MCP-compatible tool to fetch real-time stock data and perform detailed analysis on the server side. This example showcases how the template can be used to build robust, scalable solutions that enhance user experience by offloading processing tasks from the client.
Developing a language translation service where text is sent from an AI application, processed through an MCP-compliant server, and translated before being returned. This use case highlights the template’s ability to handle complex, asynchronous operations seamlessly.
The MCP Server Template supports integration with various MCP clients, offering full compatibility with Claude Desktop, Continue, Cursor, and more. The table below outlines MCP client support details:
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ (Tools Only) | ✅ | ❌ (Prompts Limited) | Tools Only |
To ensure optimal performance and compatibility, consider the following matrix when integrating this MCP server template into your project:
Tool Capability Level | MCP Client |
---|---|
High | Claude Desktop, Continue |
Medium | Cursor |
Low | Unsupported |
Below is a sample MCP configuration snippet for the template:
{
"mcpServers": {
"exampleTool": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-example"],
"env": {
"API_KEY": "your-api-key"
}
}
}
}
To enhance security, consider implementing access controls and secure token management:
// example in TypeScript
import { createServer } from 'http';
import { parseRequestHeaders } from '@modelcontextprotocol/utils';
const server = createServer((req, res) => {
const headers = parseRequestHeaders(req.headers);
if (!headers.authToken || !isValidAuthToken(headers.authToken)) {
return res.writeHead(401).end();
}
// Proceed with logic
});
server.listen(port, () => console.log(`Listening on port ${port}`));
A: Ensure your tool adheres to the protocol specification detailed by MCP and test thoroughly across supported clients like Claude Desktop and Continue.
A: Use session management or context passing mechanisms provided by the MCP SDK to maintain consistent state across multiple requests.
A: Implement robust authentication (e.g., JWT tokens) and authorization checks at each API entry point.
A: Yes, combine multiple tools or services using the DataProcessor
interface and register them in the server configuration.
A: The template provides clear guidelines on how to adapt existing codebases. Follow the example structure closely for a smoother integration process.
To contribute to the MCP Server Template:
git clone https://github.com/your-username/mcp-server-template.git
cd mcp-server-template
For more information on the Model Context Protocol (MCP) ecosystem and relevant resources, visit:
By leveraging this template, developers can build robust, scalable, and compatible MCP servers that integrate seamlessly into the broader AI application landscape.
RuinedFooocus is a local AI image generator and chatbot image server for seamless creative control
Learn to set up MCP Airflow Database server for efficient database interactions and querying airflow data
Simplify MySQL queries with Java-based MysqlMcpServer for easy standard input-output communication
Build stunning one-page websites track engagement create QR codes monetize content easily with Acalytica
Access NASA APIs for space data, images, asteroids, weather, and exoplanets via MCP integration
Explore CoRT MCP server for advanced self-arguing AI with multi-LLM inference and enhanced evaluation methods